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arXiv · 2209.06416

ImageArg: A Multi-modal Tweet Dataset for Image Persuasiveness Mining

Zhexiong Liu·Meiqi Guo·Yue Dai·Diane Litman
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Abstract

The growing interest in developing corpora of persuasive texts has promoted applications in automated systems, e.g., debating and essay scoring systems; however, there is little prior work mining image persuasiveness from an argumentative perspective. To expand persuasiveness mining into a multi-modal realm, we present a multi-modal dataset, ImageArg, consisting of annotations of image persuasiveness in tweets. The annotations are based on a persuasion taxonomy we developed to explore image functionalities and the means of persuasion. We benchmark image persuasiveness tasks on ImageArg using widely-used multi-modal learning methods. The experimental results show that our dataset offers a useful resource for this rich and challenging topic, and there is ample room for modeling improvement.

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Zhexiong Liu, Meiqi Guo, Yue Dai, Diane Litman. 2022-09-14. ImageArg: A Multi-modal Tweet Dataset for Image Persuasiveness Mining. https://arxiv.org/abs/2209.06416

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